---
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-960h-lv60-self-with-wikipedia-lm-timit
  results: []
---

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# wav2vec2-large-960h-lv60-self-with-wikipedia-lm-timit

This model is a fine-tuned version of [gxbag/wav2vec2-large-960h-lv60-self-with-wikipedia-lm](https://huggingface.co/gxbag/wav2vec2-large-960h-lv60-self-with-wikipedia-lm) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0889
- Wer: 0.4976

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 7.7911        | 2.02  | 250  | 3.0896          | 1.0    |
| 1.3854        | 4.03  | 500  | 0.0704          | 0.5052 |
| 0.1926        | 6.05  | 750  | 0.0678          | 0.5010 |
| 0.1472        | 8.06  | 1000 | 0.0794          | 0.5157 |
| 0.1326        | 10.08 | 1250 | 0.0937          | 0.5031 |
| 0.104         | 12.1  | 1500 | 0.0859          | 0.5055 |
| 0.0754        | 14.11 | 1750 | 0.0903          | 0.5031 |
| 0.0624        | 16.13 | 2000 | 0.0927          | 0.5034 |
| 0.0594        | 18.14 | 2250 | 0.0929          | 0.5016 |
| 0.057         | 20.16 | 2500 | 0.0873          | 0.5039 |
| 0.0476        | 22.18 | 2750 | 0.0974          | 0.5055 |
| 0.0382        | 24.19 | 3000 | 0.0886          | 0.5003 |
| 0.0329        | 26.21 | 3250 | 0.0832          | 0.4987 |
| 0.032         | 28.22 | 3500 | 0.0889          | 0.4976 |


### Framework versions

- Transformers 4.23.0.dev0
- Pytorch 1.13.0.dev20220624+cu113
- Datasets 2.5.2.dev0
- Tokenizers 0.12.1